近十幾年來ETF市場蓬勃發展，自2003年起至2018年全球ETF市場如火如荼，亞洲地區雖然起步較歐美地區稍晚，成長速度並不遜色於歐美兩區，中國市場是近年來全球市場資金的聚集地，各項金融商品在中國市場的表現對於亞洲市場均具一定的指標性意涵，尤其是同為成長快速的ETF，因此本論文將以中國市場作探討，由於ETF市場上充斥眾多名稱、標的相同，但其性質及投資組合內容不同的ETF，投資人無法直接辨別其差異性，甚至買入與投資人目的不同的投資標的，為了檢驗市場上的ETF是否具有異質性，樣本為中國市場174檔ETF，期間為2009年4月至2019年3月，本研究使用Panel VAR模型檢測市場上的ETF，並使用臨摹投資組合(Mimicking portfolio)進行投資組合的編組，再以Fama and French (1993)四因子模型作為架構並加入動能因子(MOM)進一步檢測這些具有異質性的ETF是否隱含超額報酬? 
　　實證結果顯示，這些在市場上的ETF中，確實存在價量互相影響之ETF，並在經過編排後的投資組合ETF確實存在超額報酬，而影響投資組合比重最重的因子為市價淨值比，因此投資人應選擇市價低且每股淨資產高的ETF進行投資，另外也發現在風險事件下，正報酬投資組合的投資人受風險情緒影響較負報酬投資組合的投資人要大，推測正報酬投資組合的投資人轉變為風險趨避者，因此在風險事件下會盡可能拋售手中ETF以保有獲利，也因此造成ETF折價情形，而負報酬投資組合的投資人則轉變為風險愛好者，緊握手中ETF，而ETF為追蹤目標標的大盤，在風險事件過後將一定程度回歸至原有價格水準，因此風險事件下對於負報酬投資組合的投資人影響較小。

This paper mainly studies China’s ETF market. The ETF market is full of ETFs with similar names and themes, but their nature and portfolio content are different, and investors can't directly discern their differences and even buy different investment targets than investors. To test whether ETFs in the market have heterogeneity, this paper uses the Panel VAR model to detect ETFs and uses the Mimicking portfolio to group portfolios. Then using Fama and French (1993) three-factor model as a framework and adding momentum (MOM) to further test whether these heterogeneous ETFs imply excess return. The data samples were taken from 174 ETFs in the Chinese market from April 2009 to March 2019.
 　　The empirical results show that there is indeed excess return in the portfolio of ETFs after using the Mimicking portfolio, and the factor that affects the heaviest component of the portfolio is the book-to-market factor. Therefore, investors should choose ETFs with low market prices and high net assets per share for investment. In addition, we also find that under the risk event, investors with positive return on portfolios are more affected by risk sentiment than investors with negative return on portfolios. However, the investors with negative return on portfolios are transformed into risk lover.

目錄

第一章  緒論	1
第一節　全球股票型基金市場的發展現況	1
第二節　研究動機	4
第三節　研究目的的提出	6
第四節　研究架構	7
第二章　文獻回顧	9
第一節  ETF市場與現貨市場的連動關聯性	9
第二節  ETF的風險分散效益	12
第三節　總體環境變化與ETF商品的資訊傳遞功能	14
第三章　研究方法	16
第一節　變數定義	16
第二節　單根檢定和Granger因果關係檢定	19
第三節　Panel VAR向量自我迴歸模型	22
第四節　四因子超額報酬迴歸模型	25
第五節　資料來源及篩選	26
第四章　研究實證結果及分析	29
第一節　單根檢定和Granger因果關係檢定	29
第二節　VAR模型	31
第三節　Mimicking  Portfolio投資組合估計和異常報酬	35
第五章  結論	37
參考文獻	38


圖目錄

圖 1-1-1 全球ETF市場規模成長之歷史走勢圖	2
圖 1-1-2 ETF市值成長率圖                 3
圖 1-4-1 研究架構流程圖            	8
圖 4-2-1 報酬率對流動性衝擊反應圖         33
圖 4-2-2 流動性對報酬率衝擊反應圖         33


表目錄

表 1-1-1 各國家或地區ETF商品首次推出時間一覽表	 1
表 3-1-1 ETF市值(Market Value) 及淨值市價比(B/M)表 17
表 3-5-1 指數型ETF基本統計分析                     27
表 3-5-2 商品型ETF基本統計分析	                 28
表 4-1-1 ADF單根檢定及PP單根檢定	                 29
表 4-1-2 Granger 因果檢定表	                 30
表 4-2-1 Panel VAR 報酬率流動性關係表	         31
表 4-2-2 預測誤差變異分解表	                 34
表 4-3-1 投資組合劃分表	                         35
表 4-3-2 Mimicking portfolio臨摹投資組合表	 36

參考文獻
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參考網站
1.	倫敦金融顧問公司，檢自Etfgi 網站   https://etfgi.com/.  
2.	ETFs.com數據，檢自http://www.exchangetradedfunds.com/platform.html. 
參考書籍
楊浩彥，郭迺鋒，林政勳. (2013) 實用財經計量方法: EViews 之應用, 第一版, 雙葉書廊有限公司.